First US Criminal Conviction for AI-Assisted Music Streaming Fraud
In a landmark case, Michael Smith, a 54-year-old resident of North Carolina, has pleaded guilty to conspiracy to commit wire fraud, marking the first-ever criminal conviction in the United States for artificial intelligence-assisted music streaming fraud. As part of his plea agreement, Smith will forfeit $8.1 million in illicit gains, according to the U.S. Attorney's Office for the Southern District of New York.
The Suburban Life and Digital Deception
Before his federal conviction, Smith led a seemingly ordinary suburban life in Charlotte, residing in a large home with his wife and six children. He had built a steady income through ownership of multiple medical clinics, served as a judge on the reality show One Shot, and authored a self-help book. However, his ambition for fame led him down a fraudulent path.
In 2013, Smith invested in musical training sessions with Jonathan Hay, a publicist offering PR consulting to aspiring musicians. Unbeknownst to many, this venture masked a sophisticated digital operation designed to exploit the music industry's royalty systems.
Anatomy of an $8.1 Million Heist
The scheme combined high-tech automation with AI-generated music. Smith collaborated with Alex Mitchell, CEO of the AI song generator startup Boomy, which allowed users to create music through customizable prompts. By 2018, Smith was receiving thousands of songs weekly from an AI music company executive.
These tracks, with obscure names like Zygophyceae and Zygopteraceae, were credited to fake artists such as Calm Force and Calorie Event. Instead of promoting the music legitimately, Smith built a private audience using bots.
On October 20, 2017, Smith emailed himself a financial breakdown revealing 52 cloud service accounts, each with 20 bot accounts on streaming platforms, totaling 1,040 bot accounts. At its peak, this network generated approximately 661,440 streams daily, yielding over $1.2 million in annual royalties.
Rise and Fall of a Fraudulent Career
In 2018, Smith and Hay released an album titled Jazz, which quickly ascended to No. 1 on the Billboard charts but vanished the following week after distributors flagged it for streaming fraud. Concurrently, Smith faced a lawsuit from staffers at his medical clinics, alleging Medicaid and Medicare fraud and money transfers to his record label, SMH Records. The case settled in 2020, requiring Smith and co-defendants to pay $900,000.
By 2022, Smith appeared to rebound, producing a song featuring Snoop Dogg and Billy Ray Cyrus and planning projects like a horror movie with RZA and an animated series. However, by 2023, his endeavors collapsed as the Mechanical Licensing Collective halted payments after confronting him about the fraud.
In September 2024, the FBI arrested Smith, alleging he used AI music generators to create a massive volume of songs. U.S. Attorney Jay Clayton stated, Smith’s brazen scheme is over, as he stands convicted of a federal crime for his AI-assisted fraud. Smith faces up to five years in prison, with sentencing scheduled for July 29.
The Broader Impact of Streaming Fraud
Streaming platforms like Amazon Music, Apple Music, Spotify, and YouTube Music pay small royalties to songwriters, singers, and rights holders for each play. Fraudulent activities divert these funds from legitimate artists to scammers, exacerbating a growing issue in the music industry.
With the rise of AI technology, streaming fraud has become rampant. Deezer, a French streaming service, reported 60,000 AI songs uploaded daily, with about 85% of streams on those tracks being fraudulent. Morgan Hayduk, co-CEO of fraud detection startup Beatdapp, estimates the problem costs the industry conservatively $1 billion annually, calling the Smith case the tip of the iceberg.
Studies vary on the scale: a 2021 report by France's National Music Center found 1-3% of all streams are fraudulent, while Beatdapp places the figure around 10%. Smith's conviction represents a significant legal reckoning for audienceless superstars who exploit digital systems.
